Converting a TensorFlow Lite Model

.. meta:: :description: Learn how to convert a model from a TensorFlow Lite format to the OpenVINO Model.

You can download a TensorFlow Lite model from Kaggle <https://www.kaggle.com/models?framework=tfLite&subtype=module,placeholder&tfhub-redirect=true>__ or Hugging Face <https://huggingface.co/models>__. To convert the model, run model conversion with the path to the .tflite model file:

.. tab-set::

.. tab-item:: Python :sync: py

  .. code-block:: py

     import openvino as ov
     ov.convert_model('your_model_file.tflite')

.. tab-item:: CLI :sync: cli

  .. code-block:: sh

     ovc your_model_file.tflite

.. note::

TensorFlow Lite model file can be loaded by openvino.Core.read_model or openvino.Core.compile_model methods by OpenVINO runtime API without preparing OpenVINO IR first. Refer to the :doc:inference example <../running-inference> for more details. Using openvino.convert_model is still recommended if model load latency matters for the inference application.

Supported TensorFlow Lite Layers ###################################

For the list of supported standard layers, refer to the :doc:Supported Operations <../../documentation/compatibility-and-support/supported-operations> page.

Supported TensorFlow Lite Models ###################################

More than eighty percent of public TensorFlow Lite models are supported from open sources Kaggle <https://www.kaggle.com/models?framework=tfLite&subtype=module,placeholder&tfhub-redirect=true>__ and MediaPipe <https://developers.google.com/mediapipe>__. Unsupported models usually have custom TensorFlow Lite operations.